foodnear-me
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@foodnear-meFind vegan Thai restaurants near Brooklyn Bridge and get a menu for the top result."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Food Near Me — MCP Server
Model Context Protocol server for AI-native restaurant discovery — three-tier search (verified → menu_indexed → discovered), Menu Protocol menus, and structured menu validation. Plug into Claude Desktop, Cursor, ChatGPT, or any MCP host in about 30 seconds.
Production endpoint: https://foodnear.me/mcp · 8 tools · 4 resources · 3 prompts · No API key (beta)
Quick start {#quick-start}
1. Add this to your MCP host config
Cursor — ~/.cursor/mcp.json (macOS/Linux) or %USERPROFILE%\.cursor\mcp.json (Windows)
Claude Desktop — ~/Library/Application Support/Claude/claude_desktop_config.json (macOS), %APPDATA%\Claude\claude_desktop_config.json (Windows)
{
"mcpServers": {
"foodnear-me": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://foodnear.me/mcp"]
}
}
}2. Restart your MCP host
3. Try a prompt
“Find vegan Thai restaurants near Brooklyn Bridge and show me a menu for the top result.”
Your agent should call search_restaurants → get_menu (or get_restaurant first).
Related MCP server: OrderFood MCP
What you get
Tools (8)
Tool | Description |
| Three-tier geo search by |
| Restaurant profile with Schema.org JSON-LD + Menu Protocol extensions |
| Full Menu Protocol v1.0 menu (dietary flags, allergens, signatures) |
| ADO score factors and improvement recommendations |
| Validate a Menu Protocol JSON payload before publish |
| Composite: bucketed neighborhood overview ( |
| Composite: compare 2–5 known restaurants by dietary-eligible menu items and trust tier ranking |
| Composite: route-adjacent restaurant discovery between origin/destination with optional dietary ranking |
Resources (4)
URI | Content |
| Menu Protocol v1.0 specification |
| OpenAPI 3.1 spec pointer |
| Agent skill summary |
| Example search → menu flow |
Prompts (3)
Prompt | Args | Guides agent to |
|
|
|
|
|
|
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|
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Configuration
Setting | Value |
MCP URL |
|
Transport | HTTP JSON-RPC ( |
Auth | None during beta (rate limits apply) |
Registry |
|
Preview / local: Replace the URL with http://localhost:3000/mcp when running npm run dev in apps/web.
Operational tool filter: set FNM_MCP_ENABLED_TOOLS=search_restaurants,get_menu to expose only a comma-separated subset in tools/list and GET /mcp. Leave unset or * to expose all tools. This is for temporary degradation/context control, not privacy or auth.
Architecture
┌─────────────────────┐ POST /mcp (JSON-RPC) ┌─────────────────────────┐
│ MCP host │ ────────────────────────────▶│ apps/web/app/mcp │
│ (Cursor / Claude) │ GET /mcp (discovery) │ Next.js route handler │
└─────────────────────┘ └────────────┬────────────┘
│
▼
┌─────────────────────────┐
│ Supabase + PostGIS │
│ Menu Protocol (MP) │
└─────────────────────────┘Implementation: apps/web/app/mcp/route.ts · Flow runner: apps/web/lib/mcp/mcp-flow-runner.ts
Tool error contract
Failed tools/call responses include structured metadata in _meta.error:
Field | Meaning |
|
|
| What went wrong |
| How to fix the request |
| Whether the agent should retry |
|
Human-readable text is still in content[0].text for hosts that ignore _meta.
Verify
From repo root (with apps/web dev server running for localhost):
# Automated agent flows (14 flows when Supabase + seed configured; 11 without DB)
npm run test:mcp-flows
# Against production
npm run test:mcp-flows:http
# Discovery GETs + MCP tools/list count
npm run smoke:mcp
# Three-tier trust model copy parity (local files)
npm run check:discovery-copy
# Full deploy gate (13 checks + discovery copy on production URL)
npm run preflight -w web
# or: ./apps/web/scripts/deploy-preflight.sh https://foodnear.meProduction monitoring: GitHub Actions workflow MCP Production Smoke runs smoke:mcp daily and on manual dispatch (.github/workflows/mcp-smoke.yml).
Agent discovery
File | URL |
| |
| |
MCP manifest | |
AgentRoot | |
Skill file | |
OpenAPI | |
Web quick reference |
Scripted flows: apps/web/docs/example-agent-flows.md
Data trust model (three-tier search)
search_restaurantsreturns verified → menu_indexed → discovered.Every result includes
verification_statusandmenu_available. Callget_menuonly whenmenu_availableis true.Verified — owner-approved MP; authoritative for dietary/allergen claims.
menu_indexed — automated/public MP menu; cite with caveat — not owner-verified.
discovered — place only; do not cite menu items.
Trust progression:
discovered→menu_indexed→verified. See https://foodnear.me/attribution for data sources.
FAQ
Do I need an API key?
No for beta MCP access. Future paid tiers may use API keys or x402 (USDC on Base). See x402-prepaid-spec.md in your local docs/Food Near Me playbook.
Tools not showing after restart?
Confirm the config URL ends with /mcp. Restart the host completely. Run npm run smoke:mcp against your target base URL.
Empty search results?
Beta verified menus are seeded for specific metros (e.g. Williamsburg, NYC). 7 menu_indexed restaurants in Williamsburg have automated menus from website ingest. Discovered place listings cover many US metros — use coordinates in an imported region. Demo coords: 40.7128, -74.006. Run npm run db:seed -w web locally for verified test data.
Cursor vs Claude config path?
See Quick start above — each host uses a different JSON file; only the mcpServers block matters.
How is this different from DoorDash / Uber Eats APIs?
We expose owner-verified Menu Protocol data for agents — not scraped aggregator menus or ordering checkout.
Monorepo layout
This repository ships the MCP server inside the foodnear.me web app:
Path | Purpose |
Next.js app — MCP at | |
Menu Protocol schema + validators | |
Migrations, seeds, schema | |
Official MCP Registry metadata |
Business strategy and runbooks live in a separate local docs folder (not in this repo) — see your team's docs/Food Near Me playbook.
Development
npm install
cd apps/web && cp .env.example .env.local # Supabase keys
npm run dev # http://localhost:3000
npm run test:mcp-flows # POST localhost:3000/mcpOperator: menu_indexed website ingest
Promote discovered → menu_indexed via free website/ordering-platform parsers (ChowNow API, order.online, Sauce, Squarespace, BentoBox, Toast, Playwright). Always dry-run first — headless is slow.
cd apps/web
npm run db:probe:menu-batch -- --headless --limit=10
npm run db:import:menu-indexed:website:headless:dry-run -- --limit=10
npm run db:import:menu-indexed:website:headless -- --limit=10 # liveNo Uber Eats / DoorDash / Grubhub / RapidAPI scrapers. See apps/web/docs/example-agent-flows.md.
Links
Website: https://foodnear.me
Menu Protocol spec: https://github.com/foodnearme/menu-protocol
Support: https://foodnear.me/support · api@foodnear.me
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